{
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"
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"
    }
   },
   "cell_type": "markdown",
   "id": "d66888ae",
   "metadata": {},
   "source": [
    "# 数据分析咖哥十话\n",
    "\n",
    "## 第3话 获客成本何其高：回归预测用户LTV\n",
    "\n",
    "**题解** 最基本的回归分析方法是线性回归(linear regression)，它是通过线性函数对变量间定量关系进行统计分析。比如广告的投入金额与获客数量，就可能呈现出线性关系\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "<center>广告投入/新注册用户数</center>\n",
    "\n",
    "**详细内容请参考拙作：《数据分析咖哥十话》** 人民邮电出版社2022年出版\n",
    "![image-2.png](attachment:image-2.png)\n",
    "购书链接：https://item.jd.com/13335199.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "de75f28f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>订单号</th>\n",
       "      <th>产品码</th>\n",
       "      <th>消费日期</th>\n",
       "      <th>产品说明</th>\n",
       "      <th>数量</th>\n",
       "      <th>单价</th>\n",
       "      <th>用户码</th>\n",
       "      <th>城市</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536374</td>\n",
       "      <td>21258</td>\n",
       "      <td>6/1/2022 9:09</td>\n",
       "      <td>绿联usb分线器 一拖四</td>\n",
       "      <td>32</td>\n",
       "      <td>10.95</td>\n",
       "      <td>15100</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536376</td>\n",
       "      <td>22114</td>\n",
       "      <td>6/1/2022 9:32</td>\n",
       "      <td>加大男装T恤男大码胖子宽松卡</td>\n",
       "      <td>48</td>\n",
       "      <td>50.45</td>\n",
       "      <td>15291</td>\n",
       "      <td>上海</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536376</td>\n",
       "      <td>21733</td>\n",
       "      <td>6/1/2022 9:32</td>\n",
       "      <td>唐装男夏季青年棉麻中国风加肥</td>\n",
       "      <td>64</td>\n",
       "      <td>86.55</td>\n",
       "      <td>15291</td>\n",
       "      <td>上海</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536378</td>\n",
       "      <td>22386</td>\n",
       "      <td>6/1/2022 9:37</td>\n",
       "      <td>越南进口白心火龙果4个装</td>\n",
       "      <td>10</td>\n",
       "      <td>108.95</td>\n",
       "      <td>14688</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536378</td>\n",
       "      <td>85099C</td>\n",
       "      <td>6/1/2022 9:37</td>\n",
       "      <td>大连美早樱桃400g 果径约26mm</td>\n",
       "      <td>10</td>\n",
       "      <td>166.95</td>\n",
       "      <td>14688</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87175</th>\n",
       "      <td>581585</td>\n",
       "      <td>21684</td>\n",
       "      <td>6/9/2023 12:31</td>\n",
       "      <td>SMALL MEDINA STAMPED METAL BOWL</td>\n",
       "      <td>12</td>\n",
       "      <td>0.85</td>\n",
       "      <td>15804</td>\n",
       "      <td>深圳</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87176</th>\n",
       "      <td>581585</td>\n",
       "      <td>22398</td>\n",
       "      <td>6/9/2023 12:31</td>\n",
       "      <td>MAGNETS PACK OF 4 SWALLOWS</td>\n",
       "      <td>12</td>\n",
       "      <td>0.39</td>\n",
       "      <td>15804</td>\n",
       "      <td>深圳</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87177</th>\n",
       "      <td>581585</td>\n",
       "      <td>23328</td>\n",
       "      <td>6/9/2023 12:31</td>\n",
       "      <td>SET 6 SCHOOL MILK BOTTLES IN CRATE</td>\n",
       "      <td>4</td>\n",
       "      <td>3.75</td>\n",
       "      <td>15804</td>\n",
       "      <td>深圳</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87178</th>\n",
       "      <td>581585</td>\n",
       "      <td>23145</td>\n",
       "      <td>6/9/2023 12:31</td>\n",
       "      <td>ZINC T-LIGHT HOLDER STAR LARGE</td>\n",
       "      <td>12</td>\n",
       "      <td>0.95</td>\n",
       "      <td>15804</td>\n",
       "      <td>深圳</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87179</th>\n",
       "      <td>581585</td>\n",
       "      <td>22466</td>\n",
       "      <td>6/9/2023 12:31</td>\n",
       "      <td>FAIRY TALE COTTAGE NIGHT LIGHT</td>\n",
       "      <td>12</td>\n",
       "      <td>1.95</td>\n",
       "      <td>15804</td>\n",
       "      <td>深圳</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>87180 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          订单号     产品码            消费日期                                产品说明  数量  \\\n",
       "0      536374   21258   6/1/2022 9:09                        绿联usb分线器 一拖四  32   \n",
       "1      536376   22114   6/1/2022 9:32                      加大男装T恤男大码胖子宽松卡  48   \n",
       "2      536376   21733   6/1/2022 9:32                      唐装男夏季青年棉麻中国风加肥  64   \n",
       "3      536378   22386   6/1/2022 9:37                        越南进口白心火龙果4个装  10   \n",
       "4      536378  85099C   6/1/2022 9:37                  大连美早樱桃400g 果径约26mm  10   \n",
       "...       ...     ...             ...                                 ...  ..   \n",
       "87175  581585   21684  6/9/2023 12:31    SMALL MEDINA STAMPED METAL BOWL   12   \n",
       "87176  581585   22398  6/9/2023 12:31          MAGNETS PACK OF 4 SWALLOWS  12   \n",
       "87177  581585   23328  6/9/2023 12:31  SET 6 SCHOOL MILK BOTTLES IN CRATE   4   \n",
       "87178  581585   23145  6/9/2023 12:31      ZINC T-LIGHT HOLDER STAR LARGE  12   \n",
       "87179  581585   22466  6/9/2023 12:31      FAIRY TALE COTTAGE NIGHT LIGHT  12   \n",
       "\n",
       "           单价    用户码  城市  \n",
       "0       10.95  15100  北京  \n",
       "1       50.45  15291  上海  \n",
       "2       86.55  15291  上海  \n",
       "3      108.95  14688  北京  \n",
       "4      166.95  14688  北京  \n",
       "...       ...    ...  ..  \n",
       "87175    0.85  15804  深圳  \n",
       "87176    0.39  15804  深圳  \n",
       "87177    3.75  15804  深圳  \n",
       "87178    0.95  15804  深圳  \n",
       "87179    1.95  15804  深圳  \n",
       "\n",
       "[87180 rows x 8 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np # 导入NumPy\n",
    "import pandas as pd # 导入Pandas\n",
    "df_sales = pd.read_csv('电商历史订单.csv') # 导入数据集\n",
    "df_sales # 输出数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "02721dbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sales['总价'] = df_sales['数量'] * df_sales['单价'] # 计算每单的总价"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2b383ea7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "日期范围: 1/1/2023 10:11 ~ 9/9/2022 9:20\n"
     ]
    }
   ],
   "source": [
    "print('日期范围: %s ~ %s' % (df_sales['消费日期'].min(), df_sales['消费日期'].max())) # 输出日期范围（格式转换前）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "67ee71c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "日期范围: 2022-06-01 09:09:00 ~ 2023-06-09 12:31:00\n"
     ]
    }
   ],
   "source": [
    "df_sales['消费日期'] = pd.to_datetime(df_sales['消费日期']) # 转换日期格式\n",
    "print('日期范围: %s ~ %s' % (df_sales['消费日期'].min(), df_sales['消费日期'].max()))# 输出日期范围"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a8d4dc67",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>订单号</th>\n",
       "      <th>产品码</th>\n",
       "      <th>消费日期</th>\n",
       "      <th>产品说明</th>\n",
       "      <th>数量</th>\n",
       "      <th>单价</th>\n",
       "      <th>用户码</th>\n",
       "      <th>城市</th>\n",
       "      <th>总价</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536374</td>\n",
       "      <td>21258</td>\n",
       "      <td>2022-06-01 09:09:00</td>\n",
       "      <td>绿联usb分线器 一拖四</td>\n",
       "      <td>32</td>\n",
       "      <td>10.95</td>\n",
       "      <td>15100</td>\n",
       "      <td>北京</td>\n",
       "      <td>350.4</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536376</td>\n",
       "      <td>22114</td>\n",
       "      <td>2022-06-01 09:32:00</td>\n",
       "      <td>加大男装T恤男大码胖子宽松卡</td>\n",
       "      <td>48</td>\n",
       "      <td>50.45</td>\n",
       "      <td>15291</td>\n",
       "      <td>上海</td>\n",
       "      <td>2421.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536376</td>\n",
       "      <td>21733</td>\n",
       "      <td>2022-06-01 09:32:00</td>\n",
       "      <td>唐装男夏季青年棉麻中国风加肥</td>\n",
       "      <td>64</td>\n",
       "      <td>86.55</td>\n",
       "      <td>15291</td>\n",
       "      <td>上海</td>\n",
       "      <td>5539.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536378</td>\n",
       "      <td>22386</td>\n",
       "      <td>2022-06-01 09:37:00</td>\n",
       "      <td>越南进口白心火龙果4个装</td>\n",
       "      <td>10</td>\n",
       "      <td>108.95</td>\n",
       "      <td>14688</td>\n",
       "      <td>北京</td>\n",
       "      <td>1089.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536378</td>\n",
       "      <td>85099C</td>\n",
       "      <td>2022-06-01 09:37:00</td>\n",
       "      <td>大连美早樱桃400g 果径约26mm</td>\n",
       "      <td>10</td>\n",
       "      <td>166.95</td>\n",
       "      <td>14688</td>\n",
       "      <td>北京</td>\n",
       "      <td>1669.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14837</th>\n",
       "      <td>545190</td>\n",
       "      <td>22937</td>\n",
       "      <td>2022-08-29 15:32:00</td>\n",
       "      <td>懒人居家神器-轻松剪</td>\n",
       "      <td>6</td>\n",
       "      <td>2.50</td>\n",
       "      <td>15656</td>\n",
       "      <td>苏州</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14838</th>\n",
       "      <td>545190</td>\n",
       "      <td>22722</td>\n",
       "      <td>2022-08-29 15:32:00</td>\n",
       "      <td>金属色气球2.8g结婚房布置</td>\n",
       "      <td>40</td>\n",
       "      <td>3.00</td>\n",
       "      <td>15656</td>\n",
       "      <td>苏州</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14839</th>\n",
       "      <td>545190</td>\n",
       "      <td>22457</td>\n",
       "      <td>2022-08-29 15:32:00</td>\n",
       "      <td>烘焙蛋糕装饰摆件冰雪兔插签</td>\n",
       "      <td>6</td>\n",
       "      <td>5.00</td>\n",
       "      <td>15656</td>\n",
       "      <td>苏州</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14840</th>\n",
       "      <td>545190</td>\n",
       "      <td>22464</td>\n",
       "      <td>2022-08-29 15:32:00</td>\n",
       "      <td>弟子规圣人训消防员要牢记塑封卡</td>\n",
       "      <td>12</td>\n",
       "      <td>3.00</td>\n",
       "      <td>15656</td>\n",
       "      <td>苏州</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14841</th>\n",
       "      <td>545190</td>\n",
       "      <td>22423</td>\n",
       "      <td>2022-08-29 15:32:00</td>\n",
       "      <td>黑科技天气预报风暴屏</td>\n",
       "      <td>1</td>\n",
       "      <td>22.50</td>\n",
       "      <td>15656</td>\n",
       "      <td>苏州</td>\n",
       "      <td>22.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14842 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          订单号     产品码                消费日期                产品说明  数量      单价  \\\n",
       "0      536374   21258 2022-06-01 09:09:00        绿联usb分线器 一拖四  32   10.95   \n",
       "1      536376   22114 2022-06-01 09:32:00      加大男装T恤男大码胖子宽松卡  48   50.45   \n",
       "2      536376   21733 2022-06-01 09:32:00      唐装男夏季青年棉麻中国风加肥  64   86.55   \n",
       "3      536378   22386 2022-06-01 09:37:00        越南进口白心火龙果4个装  10  108.95   \n",
       "4      536378  85099C 2022-06-01 09:37:00  大连美早樱桃400g 果径约26mm  10  166.95   \n",
       "...       ...     ...                 ...                 ...  ..     ...   \n",
       "14837  545190   22937 2022-08-29 15:32:00          懒人居家神器-轻松剪   6    2.50   \n",
       "14838  545190   22722 2022-08-29 15:32:00      金属色气球2.8g结婚房布置  40    3.00   \n",
       "14839  545190   22457 2022-08-29 15:32:00       烘焙蛋糕装饰摆件冰雪兔插签   6    5.00   \n",
       "14840  545190   22464 2022-08-29 15:32:00     弟子规圣人训消防员要牢记塑封卡  12    3.00   \n",
       "14841  545190   22423 2022-08-29 15:32:00          黑科技天气预报风暴屏   1   22.50   \n",
       "\n",
       "         用户码  城市      总价  \n",
       "0      15100  北京   350.4  \n",
       "1      15291  上海  2421.6  \n",
       "2      15291  上海  5539.2  \n",
       "3      14688  北京  1089.5  \n",
       "4      14688  北京  1669.5  \n",
       "...      ...  ..     ...  \n",
       "14837  15656  苏州    15.0  \n",
       "14838  15656  苏州   120.0  \n",
       "14839  15656  苏州    30.0  \n",
       "14840  15656  苏州    36.0  \n",
       "14841  15656  苏州    22.5  \n",
       "\n",
       "[14842 rows x 9 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sales_3m = df_sales[(df_sales. 消费日期 > '2022-06-01') & (df_sales. 消费日期 <= '2022-08-30')] # 构建仅含前3 个月数据的数据集\n",
    "df_sales_3m.reset_index(drop=True) # 重置索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5a0ebe72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "      <th>369</th>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>370 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       用户码\n",
       "0    15100\n",
       "1    15291\n",
       "2    14688\n",
       "3    15311\n",
       "4    15862\n",
       "..     ...\n",
       "365  15951\n",
       "366  14745\n",
       "367  15724\n",
       "368  15874\n",
       "369  15656\n",
       "\n",
       "[370 rows x 1 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_user_LTV = pd.DataFrame(df_sales_3m['用户码'].unique()) # 生成以“用户码”为主键的对象\n",
    "df_user_LTV.columns = ['用户码'] # 设定字段名\n",
    "df_user_LTV # 输出数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5f54cefe",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_R_value = df_sales_3m.groupby('用户码'). 消费日期.max().reset_index() # 找到每个用户的最近消费日期，构建df_R_value 对象\n",
    "df_R_value.columns = ['用户码','最近购买日期'] # 设定字段名\n",
    "df_R_value['R值'] = (df_R_value['最近购买日期'].max() - df_R_value['最近购买日期']).dt.days # 计算最新日期与上次消费日期间的天数\n",
    "df_user_LTV = pd.merge(df_user_LTV, df_R_value[['用户码','R值']], on='用户码') # 把上次消费日期距最新日期的天数（R 值）整合至df_user 对象中"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0f6efd0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_F_value = df_sales_3m.groupby('用户码'). 消费日期.count().reset_index() # 计算每个用户的消费次数，构建df_F_value 对象\n",
    "df_F_value.columns = ['用户码','F值'] # 设定字段名\n",
    "df_user_LTV = pd.merge(df_user_LTV, df_F_value[['用户码','F值']], on='用户码') # 把消费频率(F 值)整合至df_user 对象中"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "52245fbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_M_value = df_sales_3m.groupby('用户码').总价.sum().reset_index() # 计算每个用户前3 个月的消费总额，构建df_M_value 对象\n",
    "df_M_value.columns = ['用户码','M值'] # 设定字段名\n",
    "df_user_LTV = pd.merge(df_user_LTV, df_M_value, on='用户码') # 把消费总额（M 值）整合至df_user对象中"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6a044394",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>用户码</th>\n",
       "      <th>R值</th>\n",
       "      <th>F值</th>\n",
       "      <th>M值</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15100</td>\n",
       "      <td>45</td>\n",
       "      <td>7</td>\n",
       "      <td>985.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15291</td>\n",
       "      <td>35</td>\n",
       "      <td>37</td>\n",
       "      <td>16922.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14688</td>\n",
       "      <td>6</td>\n",
       "      <td>88</td>\n",
       "      <td>14700.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15311</td>\n",
       "      <td>5</td>\n",
       "      <td>717</td>\n",
       "      <td>12734.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15862</td>\n",
       "      <td>89</td>\n",
       "      <td>59</td>\n",
       "      <td>1297.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     用户码  R值   F值        M值\n",
       "0  15100  45    7    985.50\n",
       "1  15291  35   37  16922.75\n",
       "2  14688   6   88  14700.78\n",
       "3  15311   5  717  12734.66\n",
       "4  15862  89   59   1297.71"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_user_LTV.head() # 输出df_user_LTV 的前几行数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a415558b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "  <thead>\n",
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       "      <th>用户码</th>\n",
       "      <th>年度LTV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14684</td>\n",
       "      <td>1236.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14687</td>\n",
       "      <td>628.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14688</td>\n",
       "      <td>18335.88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     用户码     年度LTV\n",
       "0  14681    498.95\n",
       "1  14682     52.00\n",
       "2  14684   1236.28\n",
       "3  14687    628.38\n",
       "4  14688  18335.88"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_user_1y = df_sales.groupby('用户码')['总价'].sum().reset_index() # 计算每个用户的整年消费总额，构建df_user_1y 对象\n",
    "df_user_1y.columns = ['用户码','年度LTV'] # 设定字段名\n",
    "df_user_1y.head() # 输出前几行数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b6d57352",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>用户码</th>\n",
       "      <th>R值</th>\n",
       "      <th>F值</th>\n",
       "      <th>M值</th>\n",
       "      <th>年度LTV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15100</td>\n",
       "      <td>45</td>\n",
       "      <td>7</td>\n",
       "      <td>985.50</td>\n",
       "      <td>985.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15291</td>\n",
       "      <td>35</td>\n",
       "      <td>37</td>\n",
       "      <td>16922.75</td>\n",
       "      <td>20189.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14688</td>\n",
       "      <td>6</td>\n",
       "      <td>88</td>\n",
       "      <td>14700.78</td>\n",
       "      <td>18335.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15311</td>\n",
       "      <td>5</td>\n",
       "      <td>717</td>\n",
       "      <td>12734.66</td>\n",
       "      <td>59423.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15862</td>\n",
       "      <td>89</td>\n",
       "      <td>59</td>\n",
       "      <td>1297.71</td>\n",
       "      <td>1776.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>15951</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>375.17</td>\n",
       "      <td>669.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>366</th>\n",
       "      <td>14745</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>240.60</td>\n",
       "      <td>1167.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>367</th>\n",
       "      <td>15724</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>103.65</td>\n",
       "      <td>212.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>15874</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>584.35</td>\n",
       "      <td>4330.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>15656</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>385.10</td>\n",
       "      <td>890.65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>370 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       用户码  R值   F值        M值     年度LTV\n",
       "0    15100  45    7    985.50    985.50\n",
       "1    15291  35   37  16922.75  20189.31\n",
       "2    14688   6   88  14700.78  18335.88\n",
       "3    15311   5  717  12734.66  59423.99\n",
       "4    15862  89   59   1297.71   1776.36\n",
       "..     ...  ..  ...       ...       ...\n",
       "365  15951   1   22    375.17    669.57\n",
       "366  14745   1    7    240.60   1167.16\n",
       "367  15724   0    5    103.65    212.30\n",
       "368  15874   0    5    584.35   4330.67\n",
       "369  15656   0   15    385.10    890.65\n",
       "\n",
       "[370 rows x 5 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_LTV = pd.merge(df_user_LTV, df_user_1y, on='用户码', how='left') # 计算整体LTV，训练数据集\n",
    "df_LTV # 输出df_LTV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "803f9f2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>R值</th>\n",
       "      <th>F值</th>\n",
       "      <th>M值</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45</td>\n",
       "      <td>7</td>\n",
       "      <td>985.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35</td>\n",
       "      <td>37</td>\n",
       "      <td>16922.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>88</td>\n",
       "      <td>14700.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>717</td>\n",
       "      <td>12734.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>89</td>\n",
       "      <td>59</td>\n",
       "      <td>1297.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   R值   F值        M值\n",
       "0  45    7    985.50\n",
       "1  35   37  16922.75\n",
       "2   6   88  14700.78\n",
       "3   5  717  12734.66\n",
       "4  89   59   1297.71"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = df_LTV.drop(['用户码','年度LTV'],axis=1) # 特征集\n",
    "X.head() # 输出特征集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6390c4f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      985.50\n",
       "1    20189.31\n",
       "2    18335.88\n",
       "3    59423.99\n",
       "4     1776.36\n",
       "Name: 年度LTV, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = df_LTV['年度LTV'] # 标签集\n",
    "y.head() #输出标签集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8d7ec803",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split #导入train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=7) #拆分训练集和测试集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "bef62963",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression #导入线性回归模块\n",
    "model = LinearRegression() #创建线性回归模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0ba3ad07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X_train, y_train) #拟合模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f13b0055",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X_train, y_train) #拟合模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a352427e",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train_preds =  model.predict(X_train) # 用模型预测训练集\n",
    "y_test_preds = model.predict(X_test) # 用模型预测测试集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a2a5cc02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "R值     83.00\n",
       "F值     64.00\n",
       "M值    521.69\n",
       "Name: 80, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.iloc[2] # 随机选择一行数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "051a32b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1376.3506740578225"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test_preds[2] #模型预测值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "69770946",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1384.68"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.iloc[2] #实际值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a255a83c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "训练集上的R平方分数: 0.6187\n",
      "测试集上的R平方分数: 0.4778\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import r2_score, median_absolute_error #导入Sklearn评估模块\n",
    "print('训练集上的R平方分数: %0.4f' % r2_score(y_true=y_train, y_pred=y_train_preds))\n",
    "print('测试集上的R平方分数: %0.4f' % r2_score(y_true=y_test, y_pred=y_test_preds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b521442e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, ' 实际值与预测值')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt # 导入Matplotlib 的pyplot 模块\n",
    "plt.rcParams[\"font.family\"]=['SimHei'] #用来设定字体样式\n",
    "plt.rcParams['font.sans-serif']=['SimHei'] #用来设定无衬线字体样式\n",
    "plt.rcParams['axes.unicode_minus']=False #用来正常显示负号\n",
    "plt.scatter(y_test, y_test_preds) # 预测值和实际值的散点图\n",
    "plt.plot([0, max(y_test)], [0, max(y_test_preds)], color='gray', lw=1, linestyle='--') # 绘图\n",
    "plt.xlabel(' 实际值') #x 轴\n",
    "plt.ylabel(' 预测值') #y 轴\n",
    "plt.title(' 实际值与预测值') # 标题"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4b8b550",
   "metadata": {},
   "source": [
    "**就到这里！下面请大家自行研习更多算法，并加以比较**\n",
    "\n",
    "scikit-learn中可应用于解决回归问题的算法很多，并不仅限于线性回归。就本例而言，大家还可以尝试使用SVM、决策树、集成学习等模型。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
